Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients

机译：变系数广义线性随机效应模型两成分混合的蒙特卡洛EM算法

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Generalized linear models have many applications in agriculture, biology, and so on. With the need of applications, it was extended from various ways for more general cases. The paper proposes an extended finite mixture of generalized linear random effects models (GLMMs) with Varying Coefficients, based on the finite mixture distribution and GLMMs with varying coefficients, then parameters are estimated via Monte Carlo EM (MCEM) algorithm.

机译：广义线性模型在农业，生物学等方面有许多应用。随着应用程序的需要，它从各种方式扩展到了更一般的情况。提出了一种基于变系数的广义线性随机效应模型（GLMM）的扩展有限混合，基于有限混合分布和具有变化系数的GLMM，然后通过蒙特卡洛EM（MCEM）算法对参数进行估计。

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《2011 International Conference on Electronic Mechanical Engineering and Information Technology》|2011年|p.17-20|共4页
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Zhou Xingcai; Tan Changchun;
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中图分类计算机的应用;
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EM algorithm; Generalized linear models; Monte Carlo; Random effects; Varying coefficients;

机译：EM算法广义线性模型蒙特卡洛随机效应变系数;

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专利

1. Generalized linear random effects models with varying coefficients [J] . Gerhard Tutz, Goran Kauermann Computational statistics & data analysis . 2003,第1期

机译：系数变化的广义线性随机效应模型
2. Estimation of a generalized random-effects model: some ECME algorithms and Monte Carlo evidence [J] . Robert F. Phillips Journal of Economic Dynamics and Control . 2004,第9期

机译：广义随机效应模型的估计：一些ECME算法和蒙特卡洛证据
3. Computationally efficient Monte Carlo EM algorithms for generalized linear mixed models [J] . YI-HAU CHEN Journal of statistical computation and simulation . 2006,第9期

机译：广义线性混合模型的计算有效Monte Carlo EM算法
4. Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients [C] . Zhou Xingcai, Tan Changchun International Conference on Electronic and Mechanical Engineering and Information Technology . 2011

机译：具有不同系数的广义线性随机效果模型的双组分混合物的蒙特卡罗EM算法
5. Quantum virial coefficients via path integral Monte Carlo: Theory and development of novel algorithms. [D] . Subramanian, Ramachandran. 2016

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6. Nonlinear Random Effects Mixture Models: Maximum Likelihood Estimation via the EM Algorithm [O] . Xiaoning Wang, Alan Schumitzky, David Z. D’Argenio -1

机译：非线性随机效应混合模型：通过EM算法的最大似然估计
7. Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study. [O] . Rodríguez Poo, Juan Manuel, Soberón Velez, Alexandra Pilar 2015

机译：具有固定效应的半参数面板数据变化系数模型中的差分技术：蒙特卡洛研究。

Monte Carlo EM algorithm for two-component mixture of generalized linear random effects models with varying coefficients

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